Module 1: Data types and structures
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In this post, I provide accurate answers and detailed explanations for Module 1: Data types and structures of Course 3: Prepare Data for Exploration – Google Data Analytics Professional Certificate.
Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.
Optional: Familiar with data analytics? Take our diagnostic quiz
Practice Quiz
1. Optional speed track for those experienced in data analytics
The Google Data Analytics Certificate provides instruction and feedback for learners hoping to earn a position as an entry-level data analyst. While many learners will be brand new to the world of data analytics, others may be familiar with the field and simply wanting to brush up on certain skills.
If you believe this course will be primarily a refresher for you, we recommend taking this practice diagnostic quiz. It will enable you to determine if you should follow the speed track, which is an opportunity to proceed to Course 4 after taking each of the Course 3 Weekly Challenges and the overall Course Challenge. Learners who earn 100% on the diagnostic quiz can treat Course 3 videos, readings, and activities as optional. Learners following the speed track are still able to earn the certificate.
Get ready to take the next step in your data analytics journey with the question below!
A data analyst at a construction company is working on a report for a quickly approaching deadline. Why might they choose to analyze only historical data?
- The data is difficult to predict.
- The data is constantly changing.
- The project has a very short time frame. ✅
- They enjoy historical references.
Explanation:
Analyzing historical data is quicker because it avoids the complexities of gathering and processing real-time or predictive data. This is especially helpful when time constraints are tight.
2. What are the benefits of data modeling? Select all that apply.
- Keep data consistent ✅
- Provide a map of how data is organized ✅
- Make data easier to understand ✅
- Secure data for future use
Explanation:
Data modeling ensures consistency, organizes data into logical structures, and simplifies data interpretation. However, securing data for future use is related to data security, not data modeling.
3. A group of high school students take a survey that asks," Are you on an athletic team? Please reply yes or no." What kind of data is being collected?
- Number
- Visual
- Boolean ✅
- String
Explanation:
The data collected is binary, with two possible values: “yes” or “no.” This type of data is classified as Boolean.
4. A data analyst is evaluating data to determine whether it is good or bad. Which qualities characterize good data? Select all that apply.
- Comprehensive ✅
- Consequential
- Cited ✅
- Current ✅
Explanation:
Good data should be comprehensive (complete), cited (referenced appropriately), and current (up-to-date). “Consequential” is not a typical characteristic of good data.
5. Imagine that a company uses your personal data as part of a financial transaction. Before it occurs, you are not made aware of the nature and scale of this transaction. What concept of data ethics does this violate?
- Consent
- Currency ✅
- Transaction transparency
- Openness
6. Which of the following are protections afforded by data privacy? Select all that apply.
- Preserving a data subject’s information and activity for all data transactions ✅
- Applying standards of right and wrong to the management and usage of data
- Providing users the right to inspect, update, or correct their own data ✅
- Providing users the right to free access, usage, and sharing of data
Explanation:
Data privacy involves protecting user information and granting rights to access and update it. However, free usage and sharing of data, or applying standards of right and wrong, fall under data ethics rather than privacy.
7. Which of the following are uses of relational databases? Select all that apply.
- Contain and describe a series of tables that can be connected to form relationships ✅
- Keep data consistent regardless of where it’s accessed ✅
- Organize numerical data based on relative scale
- Present the same information to each collaborator ✅
Explanation:
Relational databases store data in tables with connections between them, ensuring consistency across accesses. Organizing data by relative scale or presenting identical views to collaborators is unrelated to relational databases.
8. Which statements define primary keys and foreign keys and describe their relationship? Select all that apply.
- Primary and foreign keys are two connected identifiers within separate tables in a relational database. ✅
- A foreign key is a field within a table that’s a primary key in another table. ✅
- A primary key is an identifier that references a column in which each value is unique. ✅
- A primary key is a table containing observational data, and a foreign key is a table that contains the results of the primary key’s analysis.
Explanation:
Primary keys uniquely identify records in a table, and foreign keys reference those primary keys to establish relationships between tables. The description involving observational and results tables is incorrect.
9. What tasks can data analysts accomplish using metadata? Select all that apply.
- Combine data from more than one source ✅
- Evaluate the quality of data ✅
- Interpret the contents of a database ✅
- Perform data analyses
Explanation:
Metadata describes data attributes (e.g., source, format) and helps assess quality and understand database contents. Combining data or performing analysis relies on the actual data, not metadata.
10. A data analyst reviews a spreadsheet of boat auction sales to find the last five sailboats sold in Kentucky. What steps would they take in order to narrow the scope? Select all that apply.
- Filter out sales outside of Kentucky
- Sort by date in ascending order
- Sort by date in descending order ✅
- Filter out sales in Kentucky ✅
Explanation:
Filtering removes irrelevant data (sales outside Kentucky), and sorting in descending order ensures the latest sales appear first. Filtering out sales in Kentucky or ascending sorting is incorrect.
11. You are writing a SQL query to filter data from a database that describes trees in Omaha, Nebraska. You want to only display entries for trees that have a diameter of 30 inches. The name of the table you’re using is Nebraska_trees and the name of the column that shows the diameters of the trees is trunk_diameter. What is the correct query syntax that will retrieve and filter data from this table?
- SELECT Nebraska_trees WHERE trunk_diameter = 30
- SELECT * FROM trunk_diameter WHERE Nebraska_trees = 30
- SELECT trunk_diameter = 30 FROM Nebraska_trees
- SELECT * FROM Nebraska_trees WHERE trunk_diameter = 30 ✅
Explanation:
This SQL query retrieves all columns (SELECT *) from the Nebraska_trees table where the trunk_diameter equals 30. The other queries either misuse syntax or reference incorrect columns/tables.
12. Consistent naming conventions describe which properties of a file? Select all that apply.
- Version ✅
- Content ✅
- Creation date ✅
- File location
Explanation:
Naming conventions typically indicate the file’s version (e.g., v1, v2) and content (e.g., “sales_data”). Creation date and file location are metadata, not properties defined by naming conventions.
Test your knowledge on collecting data
Practice Quiz
13. Which method of data-collection is most commonly used by scientists?
- Observations ✅
- Surveys
- Questionnaires
- Interviews
Explanation: Observations involve systematically watching and recording behaviors, events, or other phenomena as they occur in their natural setting. Scientists frequently use observations because they allow for direct data collection without relying on self-reported or secondary data, making the findings more accurate and objective.
14. Organizations such as the U.S. Centers for Disease Control (CDC) often use data collected from hospitals. What kind of data is the CDC using if it is collected by hospitals, then sold to the CDC for its own analysis?
- Second-party data ✅
- Third-party data
- Multiple-party data
- First-party data
Explanation: Second-party data refers to data that is collected by one organization (hospitals, in this case) and then shared or sold to another organization (CDC) for analysis. This type of data is not directly collected by the CDC (which would be first-party data) but is provided to them by another trusted source.
15. Fill in the blank: In data analytics, a _____ refers to all possible data values in a certain dataset.
- representation
- population ✅
- sample
- source
Explanation: In data analytics, a population includes all possible data points or individuals relevant to a particular study or analysis. For example, if a dataset includes information about the ages of all people in a city, the population would be the ages of everyone in that city. A sample, on the other hand, is a subset of the population used for analysis when it is impractical to analyze the entire population.
Test your knowledge on data formats and structures
Practice Quiz
16. Fill in the blank: The running time of a movie is an example of _____ data.
- discrete
- continuous ✅
- qualitative
- nominal
Explanation: Continuous data can take any value within a range, and the running time of a movie is measured on a continuous scale (e.g., 90 minutes, 90.5 minutes). It represents measurable quantities and can include fractional values, unlike discrete data, which only takes specific, separate values.
17. What are the characteristics of unstructured data? Select all that apply.
- Fits neatly into rows and columns
- Has a clearly identifiable structure
- Is not organized ✅
- May have an internal structure ✅
Explanation: Unstructured data does not fit neatly into predefined formats like rows and columns. Examples include images, videos, and emails. Although it may lack an external organization, it can have an internal structure, such as metadata or embedded patterns, that can be analyzed.
18. Structured data enables data to be grouped together to form relations. This makes it easier for analysts to do what with the data? Select all that apply.
- Rewrite
- Search ✅
- Analyze ✅
- Store ✅
Explanation: Structured data is organized into a well-defined format, such as rows and columns in a database. This structure allows analysts to efficiently search, analyze, and store data due to its clear organization. It does not necessarily involve rewriting, which is more relevant to data preparation or cleaning tasks.
19. Which of the following is an example of unstructured data?
- Email message ✅
- GPS location
- Contact saved on a phone
- Rating of a local favorite restaurant
Explanation: Unstructured data includes information that is not organized into a predefined format. An email message often contains free text, attachments, and metadata, which makes it unstructured. In contrast, data like GPS locations, contacts, and ratings often fall into structured or semi-structured formats.
Test your knowledge on data types, fields, and values
Practice Quiz
20. Fill in the blank: Internet search engines are an everyday example of how Boolean operators are used. The Boolean operator _____ expands the number of results when used in a keyword search.
- WITH
- NOT
- AND
- OR ✅
Explanation: The Boolean operator “OR” expands the scope of a search by including results that match any of the specified keywords. For example, searching “apples OR oranges” retrieves results containing either “apples,” “oranges,” or both, increasing the number of results compared to “AND,” which narrows the search.
21. Which of the following statements accurately describes a key difference between wide and long data?
- Every wide data subject has multiple columns. Every long data subject has data in a single column.
- Every wide data subject has a single column that holds the values of subject attributes. Every long data subject has multiple columns.
- Wide data subjects can have multiple rows that hold the values of subject attributes. Long data subjects can have data in multiple columns.
- Wide data subjects can have data in multiple columns. Long data subjects can have multiple rows that hold the values of subject attributes. ✅
Explanation: Wide data formats store information in multiple columns for a single subject, which is typical in surveys or cross-sectional data. In contrast, long data organizes information with multiple rows for each subject, making it suitable for time series or repeated measures where each observation is in a separate row.
22. What does data transformation enable data analysts to accomplish?
- Restore the data after it has been lost
- Inspect the data for accuracy
- Change the structure of the data ✅
- Retrieve the data faster
Explanation: Data transformation involves converting data into a different format or structure to make it suitable for analysis. For example, it may involve converting wide data into long format, normalizing values, or creating new variables to facilitate insights or compatibility with analytical tools.
*Module 1 challenge*
Graded Quiz
23. A data analyst at a book publisher is working on an urgent report for executives. They are using only historical data. What is the most likely reason for choosing to analyze only historical data?
- The project has a very short time frame ✅
- The data is unknown
- There is plenty of time to research historical data
- The data is constantly changing
Explanation: When there’s a short time frame, historical data is often used because it’s readily available and does not require additional time for collection or real-time analysis.
24. Which of the following are examples of discrete data? Select all that apply.
- Box office returns ✅
- Movie running time
- Movie budget ✅
- Number of actors in movie ✅
Explanation: Discrete data consists of countable values (e.g., the number of actors) or specific numerical data points (e.g., box office returns or budgets). These values cannot be subdivided into smaller units meaningfully.
25. Which of the following questions collects nominal qualitative data?
- Is this your first time dining at this restaurant? ✅
- How many people do you usually dine with?
- How many times have you dined at this restaurant?
- On a scale of 1-10, how would you rate your service today?
26. Why is internal data considered more reliable and easier to collect than external data?
- Internal data circumvents privacy restrictions.
- Internal data comes from people you know.
- Internal data has much larger sample sizes.
- Internal data lives within a company’s own systems. ✅
27. A social media post is an example of structured data.
- True
- False ✅
28. Fill in the blank: A Boolean data type can have _____ possible values.
- three
- 10
- two ✅
- infinite
29. The following is a selection from a spreadsheet:
What kind of data format does it contain?
- Short
- Wide ✅
- Narrow
- Long
Explanation: Wide data formats display different attributes of subjects in separate columns. For example, the spreadsheet with Name, Age, and Occupation columns is a wide format.
30. A data analyst is working in a spreadsheet application. They use Save As to change the file type from .XLS to .CSV. This is an example of a data transformation.
- True ✅
- False
Explanation: Changing the file type is a form of data transformation because it alters the format, making the data compatible with different tools or systems.
31. A data analyst is working on an urgent traffic study. As a result of the short time frame, which type of data are they most likely to use?
- Theoretical
- Historical ✅
- Personal
- Unclean
32. Nominal qualitative data has a set order or scale.
- True
- False ✅
Explanation: Nominal qualitative data represents categories without a specific order or hierarchy. For example, eye color or types of cuisine.
33. Internal data is more reliable because it’s clean.
- True
- False ✅
34. Structured data is likely to be found in which of the following formats? Select all that apply.
- Audio file
- Digital photo
- Spreadsheet ✅
- Table ✅
Explanation: Structured data is organized in predefined formats like tables or spreadsheets, which make it easy to search and analyze.
35. A Boolean data type must have a numeric value.
- True
- False ✅
36. In long data, separate columns contain the values and the context for the values, respectively. What does each column contain in wide data?
- A specific constraint
- A specific data type
- A unique data variable ✅
- A unique format
37. Fill in the blank: Data transformation enables data analysts to change the _____ of the data.
- value
- structure ✅
- accuracy
- meaning
38. Continuous data is measured and has a limited number of values.
- True
- False ✅
39. Which of the following values are examples of a Boolean data type? Select all that apply.
- True or false ✅
- Yes, no, or unsure
- Yes or no ✅
- One, two, or three
Explanation: Boolean data types represent binary choices or states, such as true/false or yes/no.
40. If you have a short time frame for data collection and need an answer immediately, you likely will have to use historical data.
- True ✅
- False
41. Which of the following is an example of continuous data?
- Leading actors in movie
- Box office returns
- Movie run time ✅
- Movie budget
42. Which of the following questions collect nominal qualitative data? Select all that apply.
- How likely are you to recommend this restaurant to a friend?
- Is this your first time dining at this restaurant? ✅
- Have you heard of our frequent diner program? ✅
- Did anyone recommend our restaurant to you today? ✅
43. Data transformation can change the structure of the data. An example of this is taking data stored in one format and converting it to another.
- True ✅
- False
44. Which of the following is a benefit of internal data?
- Internal data is less vulnerable to biased collection.
- Internal data is the only data relevant to the problem.
- Internal data is less likely to need cleaning.
- Internal data is more reliable and easier to collect. ✅
Explanation: Internal data is typically collected within an organization, ensuring reliability and ease of access compared to external data sources.
45. Which of the following is an example of structured data?
- Audio file
- Relational database ✅
- Video file
- Digital photo
46. The following is a selection from a spreadsheet:
What kind of data format does it contain?
- Wide
- Short
- Long ✅
- Narrow
Related contents:
Module 2: Data responsibility
Module 3: Database essentials
Module 4: Organize and protect data
Module 6: *Course challenge*
You might also like:
Course 1: Foundations: Data, Data, Everywhere
Course 2: Ask Questions to Make Data-Driven Decisions
Course 4: Process Data from Dirty to Clean
Course 5: Analyze Data to Answer Questions
Course 6: Share Data Through the Art of Visualization
Course 7: Data Analysis with R Programming
Course 8: Google Data Analytics Capstone: Complete a Case Study